1. Field of the Invention
The present invention relates to a method and a system for detecting cardiac arrhythmias from internally and/or externally detected activity of the heart.
2. Brief Description of the Prior Art
Atrial fibrillation is a serious and common cardiac arrhythmia. Atrial fibrillation is associated with rapid, irregular atrial activation with life threatening sequelae such as stroke. The atrial activations are irregularly transmitted through the atrioventricular node leading to a correspondingly irregular sequence of ventricular activations as monitored by the ventricular interbeat (RR) intervals on the surface electrocardiogram (ECG). An RR interval is an interval between two successive heart beats. Clinically, in the surface ECG, atrial fibrillation is diagnosed by absence of P waves (normally associated with the near synchronous activation of the atria) and a rapid irregular ventricular rate. P waves are difficult to determine automatically and irregular baseline activity of the ECG is common in atrial fibrillation.
Although a number of different methods have been proposed to test for atrial fibrillation based on knowledge of the RR intervals and/or the surface ECG, the detection of atrial fibrillation based on this data nevertheless poses substantial problems (Murgatroyd, et al. “Identification of Atrial Fibrillation Episodes in Ambulatory Electrocardiographic Recordings: Validation of a Method for Obtaining Labeled R—R Interval Files,” Pacing and Clinical Electrophysiology, (1995), pp. 1315–1320). In the following description, the main strategies that have been proposed to assess atrial fibrillation based on knowledge of the RR intervals and/or ECG will be briefly reviewed.
Since RR intervals during atrial fibrillation have a larger standard deviation and a more rapid decay of the autocorrelation function, there are proposals that the standard deviation and the autocorrelation function can be used to distinguish atrial fibrillation from sinus rhythm (Bootsma, et al. “Analysis of RR Intervals in Patients with Atrial Fibrillation at Rest and During Exercise,” Circulation, (1970), pp. 783–794). Since other abnormal rhythms also have a large standard deviation of RR intervals and a rapid decay of the autocorrelation function, these methods are difficult to apply in concrete situations.
Moody and Mark (G. Moody, et al. “A New Method for Detecting Atrial Fibrillation Using R—R Intervals,” Computers in Cardiology, (1983), pp. 227–230) classify RR intervals as short, long or regular. They then construct a Markov model for the probabilities for transitions between RR intervals in each of the three different length classes. Atrial fibrillation data has typical transition probabilities not shared by normal rhythms or other arrhythmia. Although the Markov model has high sensitivity for detecting atrial fibrillation, it tends to have a relatively low predictive value of a positive test.
Pinciroli and Castelli have investigated the morphology of histograms of RR intervals collected during atrial fibrillation and other arrhythmia (F. Pinciroli, et al. “Pre-clinical Experimentation of a Quantitative Synthesis of the Local Variability in the Original R—R Interval Sequence in the Presence of Arrhythmia,” Automedica, (1986), vol.6, pp. 295–317. Pinciroli and Castelli, 1986). They demonstrated that the histograms of the ratio between successive RR intervals show characteristic differences between normal rhythm and atrial fibrillation. The histogram of the ratio between successive RR intervals is symmetrical to the mean value. No quantitative methods were proposed to quantify the symmetry or to use it to develop a quantitative test.
Since the baseline of the ECG is irregular during atrial fibrillation, Slocum (J. Slocum, et al. “Computer Detection of Atrial Fibrillation on the Surface Electrocardiogram,” Computers in Cardiolody, (1987), pp. 253–254) has proposed that the regularity of the baseline, as determined by the power spectrum of the residual ECG after subtraction of the baseline of the QRS complexes can be used to detect atrial fibrillation. This method is necessarily sensitive to small amounts of noise that might corrupt the baseline of the ECG.
Implantable ventricular and atrial defibrillators are devices that distinguish atrial and ventricular fibrillation from other rhythms. Typically, electrodes in these devices record intracardiac activity directly from the atria and ventricles. The methods that are used to detect atrial fibrillation in these devices cannot be easily applied to recordings that give information about the timing of the QRS complexes (U.S. Pat. No. 6,144,878, issued to Schroeppel on Nov. 7, 2000, U.S. Pat. No. 6,035,233 issued to Schroeppel on Mar. 7, 2000, U.S. Pat. No. 5,749,900 issued to Schroeppel on May 24, 1998, U.S. Pat. No. 6,064,906 issued to Langberg et al. on May 16, 2000, U.S. Pat. No. 5,772,604 issued to Langberg et al. on Jun. 30, 1998, U.S. Pat. No. 6,061,592 issued to Nigam on May 9, 2000, U.S. Pat. No. 5,951,592 issued to Murphy on Sep. 14, 1999, U.S. Pat. No. 5,941,831 issued to Turcoft on Aug. 24, 1999, U.S. Pat. No. 5,591,215 issued to Greenhut et al. on Jan. 7, 1997).
Analysis of a histogram of the interbeat intervals can be used to discriminate between ventricular fibrillation and ventricular tachycardia. By counting the number of beats in predetermined interval classes, an algorithm identifies a given sequence as ventricular fibrillation or ventricular tachycardia (U.S. Pat. No. 5,330,508 issued to Gunderson on Jul. 19, 1994). While this patent suggests that the invention is of value in detecting and treating atrial fibrillation (column 2, lines 29–31), it does not provide specific embodiment for detecting and treating atrial fibrillation.
Based on the foregoing review of the prior art, it is apparent that there is a need to develop a method and a system for determining whether or not a given recording is atrial fibrillation based on the timing of the QRS complexes as measured from an internal and/or external monitor. Assessment of whether a patient is in atrial fibrillation based on the timing of the QRS complexes would be extremely useful, for example, for assessing the efficacy of specific drugs on a patient fitted with a monitoring device that measures the timing of the QRS complexes.